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Published byMaría Martínez Soler Modified over 6 years ago
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f t f i i i l l i l i LAND USE AND LAND-COVER CHANGE
SOME IMPORTANT SOCIO-ECONOMIC INDICATORS FOR THE 11 MUNICIPALITIES SURROUNDING THE LAKE. M o u n t a i s $ R v e r P d G l L S f c U b A D g C p x W F B y N - h Land Use as of 1996 f RELATIONSHIP BETWEEN POPULATION-VISITORS AND WATER POLLUTION M o u n t a i s $ R v e r P d G l L S f c U b A g k x > C N h F 70% of the variance in E. Coli is explained by the regression The Model is highly significant Effect from No. of Hotels Land-Cover Change 36% of the land from the municipalities around the lake is covered with forests. 22% is planted with coffee. 84% of the land in this same area is considered suitable for forestry or perennial crops only; this is mainly due to the high slopes (>30%) and shallow soils. 48% of this land did not experience any land-cover changes in the period % of the land increased in vegetation cover (mainly as a result of a shift from corn to coffee and abandoned fields). The remaining 26% of the land decreased in vegetation cover mainly as a result of clearing mature forest to establish coffee plantations. Most water quality parameters indicate a relatively clean (non-eutrophic) lake. Oxygen levels are near saturation and water transparency is high; water pH is basic and nutrient levels are low. No pesticides were detected. The main water contaminant comes from raw sewage poured into the lake from the various towns. Presence of E. Coli (indicator of fecal contamination) is alarmingly high in the water in front of the major towns. No. of Hotels is the most significant variable Presence of E. Coli was well correlated in a multiple regression analysis with municipality population levels, number of hotels, and presence of a water treatment plant in the town. The correlation was best for the measurements taken during the dry season (data shown). The dilution effect of the rain is an additional confounding factor that reduced the significance of the regression with the variable for the rainy season. Number of hotels was the variable best correlated with levels of E. Coli. The partial regression plots to the right show the correlation with one variable when the effect from the other two variables is removed. t f i i i l l i l i Effect from Population M u n i c p a l B o r d e s ( f ) P v R U b A I t m L g - 1 2 5 6 > FECAL (E. COLI) CONTAMINATION MPN/100ml Dry Season Rainy Season Effect from Water Treatment CURRENT AND FUTURE WORK We are currently processing two more Landsat images for the area, for the years 1991 and 2001. We are looking to secure additional funding to increase the level (temporal and spatial) of sampling to test for water quality. We are planning to start a set of ecotoxicological tests. We will start a more in-depth evaluation of the institutional strength of each of the municipalities with land in the watershed. We would like to thank the following organizations for their support: U.S. AID, Fundación Solar, Amigos del Lago, The Nature Conservancy, and Autoridad para el Manejo Sustentable de la Cuenca del Lago de Atitlán.
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